Here are preliminary results of the bibliometric mapping of the 2022 Luxembourg research evaluation. Its purpose is:
The method for the research-field-mapping can be reviewed here:
The seed articles deemed representative for the active areas of research in the institution, and include authors affiliated with the institution. They can be selected in three ways:
The present analysis is based on the following seed articles:
| AU | PY | TI | JI |
|---|---|---|---|
| FAGHERAZZI G;ZHANG L;AGUAYO… | 2021 | TOWARDS PRECISION CARDIOMETABOLIC PREVENTION: RESULTS FROM A MACHINE LEARNING, SEMI-SUPERVISED CL… | SCI. REP. |
| BADIMON L;ROBINSON EL;JUSIC… | 2021 | CARDIOVASCULAR RNA MARKERS AND ARTIFICIAL INTELLIGENCE MAY IMPROVE COVID-19 OUTCOME: A POSITION P… | CARDIOVASC. RES. |
| IGLESIAS-GONZÁLEZ A;SCHAEFF… | 2021 | COMPREHENSIVE ASSESSMENT OF LOCAL POPULATION CHEMICAL EXPOSOME BY COMBINATION OF ORGANIC POLLUTAN… | EXPOS. HEALTH |
| RUIZ-CASTELL M;COROLLER GL;… | 2021 | MICRONUTRIENTS AND MARKERS OF OXIDATIVE STRESS AND INFLAMMATION RELATED TO CARDIOMETABOLIC HEALTH… | NUTRIENTS |
| MALISOUX L;DELATTRE N;URHAU… | 2020 | SHOE CUSHIONING INFLUENCES THE RUNNING INJURY RISK ACCORDING TO BODY MASS: A RANDOMIZED CONTROLLE… | AM. J. SPORTS MED. |
Here, we report the results of a LDA topic-modelling (basically, clustering on words) on all title+abstract texts.
Note: While this static vies is helpful, I recommend using the interactive LDAVis version to be found under https://daniel-hain.github.io/biblio_lux_2022/output/topic_modelling/LDAviz_lih_dph.rds/index.html#topic=1&lambda=0.60&term=. For functionality and usage, see technical description in the next tab.
Topic modeling is a type of statistical modeling for discovering the abstract “topics” that occur in a collection of documents. Latent Dirichlet Allocation (LDA, Blei et al., 2003) is an example of topic model and is used to classify text in a document to a particular topic.
LDA is a generative probabilistic model that assumes each topic is a mixture over an underlying set of words, and each document is a mixture of over a set of topic probabilities. It builds a topic per document model and words per topic model, modeled as Dirichlet distributions.
LDAvis is a web-based interactive visualisation of topics estimated using LDA (Sievert & Shirley, 2014). It provides a global view of the topics (and how they differ from each other), while at the same time allowing for a deep inspection of the terms most highly associated with each individual topic. The package extracts information from a fitted LDA topic model to inform an interactive web-based visualization. The visualisation has two basic pieces.
The left panel visualise the topics as circles in the two-dimensional plane whose centres are determined by computing the Jensen–Shannon divergence between topics, and then by using multidimensional scaling to project the inter-topic distances onto two dimensions. Each topic’s overall prevalence is encoded using the areas of the circles.
The right panel depicts a horizontal bar chart whose bars represent the individual terms that are the most useful for interpreting the currently selected topic on the left. A pair of overlaid bars represent both the corpus-wide frequency of a given term as well as the topic-specific frequency of the term.
The \(\lambda\) slider allows to rank the terms according to term relevance. By default, the terms of a topic are ranked in decreasing order according their topic-specific probability ( \(\lambda\) = 1 ). Moving the slider allows to adjust the rank of terms based on much discriminatory (or “relevant”) are for the specific topic. The suggested optimal value of \(\lambda\) is 0.6.
Note: This analysis refers the co-citation analysis,
where the cited references and not the original publications are the
unit of analysis. See tab Technical descriptionfor
additional explanations
In order to partition networks into components or clusters, we deploy a community detection technique based on the Lovain Algorithm (Blondel et al., 2008). The Lovain Algorithm is a heuristic method that attempts to optimize the modularity of communities within a network by maximizing within- and minimizing between-community connectivity. We identify the following communities = knowledge bases.
| name | dgr_int | dgr |
|---|---|---|
| Knowledge Base 1: KB 1: unlabeled (n = 832, density =13.09) | ||
| HUANG C. WANG Y. LI X. CLINICAL FEATURES OF PATIENTS INFECTED WITH 2019 NOVEL CORONAVIRUS IN WUHAN CHINA (2020) | 4408 | 4951 |
| ZHOU F. YU T. DU R. CLINICAL COURSE AND RISK FACTORS FOR MORTALITY OF ADULT INPATIENTS WITH COVID-19 IN WUHAN CHINA: A RETROSPECTIVE COHORT STUDY (… | 4325 | 4876 |
| WANG D. HU B. HU C. CLINICAL CHARACTERISTICS OF 138 HOSPITALIZED PATIENTS WITH 2019 NOVEL CORONAVIRUS-INFECTED PNEUMONIA IN WUHAN CHINA (2020) | 3543 | 3946 |
| GUO T. FAN Y. CHEN M. CARDIOVASCULAR IMPLICATIONS OF FATAL OUTCOMES OF PATIENTS WITH CORONAVIRUS DISEASE 2019 (COVID-19) | 3494 | 3947 |
| SHI S. QIN M. SHEN B. ASSOCIATION OF CARDIAC INJURY WITH MORTALITY IN HOSPITALIZED PATIENTS WITH COVID-19 IN WUHAN CHINA (2020) | 3177 | 3538 |
| CHEN N. ZHOU M. DONG X. EPIDEMIOLOGICAL AND CLINICAL CHARACTERISTICS OF 99 CASES OF 2019 NOVEL CORONAVIRUS PNEUMONIA IN WUHAN CHINA: A DESCRIPTIVE … | 2822 | 3146 |
| INCIARDI R.M. LUPI L. ZACCONE G. CARDIAC INVOLVEMENT IN A PATIENT WITH CORONAVIRUS DISEASE 2019 (COVID-19) | 2075 | 2279 |
| WU Z. MCGOOGAN J.M. CHARACTERISTICS OF AND IMPORTANT LESSONS FROM THE CORONAVIRUS DISEASE 2019 (COVID-19) | 2044 | 3842 |
| YANG X. YU Y. XU J. CLINICAL COURSE AND OUTCOMES OF CRITICALLY ILL PATIENTS WITH SARS-COV-2 PNEUMONIA IN WUHAN CHINA: A SINGLE-CENTERED RETROSPECTI… | 1690 | 1875 |
| CHEN T. WU D. CHEN H. CLINICAL CHARACTERISTICS OF 113 DECEASED PATIENTS WITH CORONAVIRUS DISEASE 2019: RETROSPECTIVE STUDY (2020) | 1530 | 1684 |
| Knowledge Base 2: KB 2: unlabeled (n = 753, density =6.29) | ||
| MILNER C.E. FERBER R. POLLARD C.D. HAMILL J. DAVIS I.S. BIOMECHANICAL FACTORS ASSOCIATED WITH TIBIAL STRESS FRACTURE IN FEMALE RUNNERS (2006) | 1003 | 1003 |
| VAN GENT R.N. SIEM D. VAN MIDDELKOOP M. VAN OS A.G. BIERMA-ZEINSTRA S.M. KOES B.W. INCIDENCE AND DETERMINANTS OF LOWER EXTREMITY RUNNING INJURIES I… | 858 | 858 |
| ZADPOOR A.A. NIKOOYAN A.A. THE RELATIONSHIP BETWEEN LOWER-EXTREMITY STRESS FRACTURES AND THE GROUND REACTION FORCE: A SYSTEMATIC REVIEW (2011) | 814 | 814 |
| DAVIS I.S. BOWSER B.J. MULLINEAUX D.R. GREATER VERTICAL IMPACT LOADING IN FEMALE RUNNERS WITH MEDICALLY DIAGNOSED INJURIES: A PROSPECTIVE INVESTIGA… | 809 | 809 |
| A SYSTEMATIC REVIEW ON RISK FACTORS AND SEX DIFFERENCES (2015) | 771 | 771 |
| YAMATO T.P. SARAGIOTTO B.T. LOPES A.D. A CONSENSUS DEFINITION OF RUNNING-RELATED INJURY IN RECREATIONAL RUNNERS: A MODIFIED DELPHI APPROACH (2015) | 762 | 762 |
| VAN DER WORP H. VRIELINK J.W. BREDEWEG S.W. DO RUNNERS WHO SUFFER INJURIES HAVE HIGHER VERTICAL GROUND REACTION FORCES THAN THOSE WHO REMAIN INJURY… | 753 | 753 |
| TAUNTON J.E. RYAN M.B. CLEMENT D.B. MCKENZIE D.C. LLOYD-SMITH D.R. ZUMBO B.D. A RETROSPECTIVE CASE-CONTROL ANALYSIS OF 2002 RUNNING INJURIES (2002) | 588 | 588 |
| KLUITENBERG B. VAN MIDDELKOOP M. DIERCKS R. VAN DER WORP H. WHAT ARE THE DIFFERENCES IN INJURY PROPORTIONS BETWEEN DIFFERENT POPULATIONS OF RUNNERS… | 539 | 539 |
| CROWELL H.P. DAVIS I.S. GAIT RETRAINING TO REDUCE LOWER EXTREMITY LOADING IN RUNNERS (2011) | 480 | 480 |
| Knowledge Base 3: KB 3: unlabeled (n = 570, density =11.71) | ||
| HUANG C. WANG Y. LI X. REN L. ZHAO J. HU Y. CLINICAL FEATURES OF PATIENTS INFECTED WITH 2019 NOVEL CORONAVIRUS IN WUHAN CHINA (2020) | 2308 | 2669 |
| ZHOU F. YU T. DU R. FAN G. LIU Y. LIU Z. CLINICAL COURSE AND RISK FACTORS FOR MORTALITY OF ADULT INPATIENTS WITH COVID-19 IN WUHAN CHINA: A RETROSP… | 1687 | 1980 |
| CHEN N. ZHOU M. DONG X. QU J. GONG F. HAN Y. EPIDEMIOLOGICAL AND CLINICAL CHARACTERISTICS OF 99 CASES OF 2019 NOVEL CORONAVIRUS PNEUMONIA IN WUHAN … | 1595 | 1808 |
| WANG D. HU B. HU C. ZHU F. LIU X. ZHANG J. CLINICAL CHARACTERISTICS OF 138 HOSPITALIZED PATIENTS WITH 2019 NOVEL CORONAVIRUS-INFECTED PNEUMONIA IN … | 1499 | 1702 |
| GUO T. FAN Y. CHEN M. WU X. ZHANG L. HE T. CARDIOVASCULAR IMPLICATIONS OF FATAL OUTCOMES OF PATIENTS WITH CORONAVIRUS DISEASE 2019 (COVID-19) | 1432 | 1749 |
| SHI S. QIN M. SHEN B. CAI Y. LIU T. YANG F. ASSOCIATION OF CARDIAC INJURY WITH MORTALITY IN HOSPITALIZED PATIENTS WITH COVID-19 IN WUHAN CHINA (2020) | 1329 | 1584 |
| TANG N. LI D. WANG X. SUN Z. ABNORMAL COAGULATION PARAMETERS ARE ASSOCIATED WITH POOR PROGNOSIS IN PATIENTS WITH NOVEL CORONAVIRUS PNEUMONIA (2020) | 845 | 2534 |
| MEHTA P. MCAULEY D.F. BROWN M. SANCHEZ E. TATTERSALL R.S. MANSON J.J. COVID-19: CONSIDER CYTOKINE STORM SYNDROMES AND IMMUNOSUPPRESSION (2020) | 845 | 1594 |
| XU Z. SHI L. WANG Y. ZHANG J. HUANG L. ZHANG C. PATHOLOGICAL FINDINGS OF COVID-19 ASSOCIATED WITH ACUTE RESPIRATORY DISTRESS SYNDROME (2020) | 685 | 774 |
| GUAN W.J. NI Z.Y. HU Y. LIANG W.H. OU C.Q. HE J.X. CLINICAL CHARACTERISTICS OF CORONAVIRUS DISEASE 2019 IN CHINA (2020) | 683 | 751 |
| Knowledge Base 4: KB 4: unlabeled (n = 465, density =13.01) | ||
| GUO T. FAN Y. CHEN M. WU X. ZHANG L. HE T. WANG H. LU Z. CARDIOVASCULAR IMPLICATIONS OF FATAL OUTCOMES OF PATIENTS WITH CORONAVIRUS DISEASE 2019 (C… | 1614 | 1953 |
| HUANG C. WANG Y. LI X. REN L. ZHAO J. HU Y. ZHANG L. CAO B. CLINICAL FEATURES OF PATIENTS INFECTED WITH 2019 NOVEL CORONAVIRUS IN WUHAN CHINA (2020) | 794 | 957 |
| RUAN Q. YANG K. WANG W. JIANG L. SONG J. CLINICAL PREDICTORS OF MORTALITY DUE TO COVID-19 BASED ON AN ANALYSIS OF DATA OF 150 PATIENTS FROM WUHAN C… | 751 | 2404 |
| ZHOU F. YU T. DU R. FAN G. LIU Y. LIU Z. XIANG J. CAO B. CLINICAL COURSE AND RISK FACTORS FOR MORTALITY OF ADULT INPATIENTS WITH COVID-19 IN WUHAN … | 687 | 802 |
| SHI S. QIN M. SHEN B. CAI Y. LIU T. YANG F. GONG W. HUANG C. ASSOCIATION OF CARDIAC INJURY WITH MORTALITY IN HOSPITALIZED PATIENTS WITH COVID-19 IN… | 672 | 768 |
| WANG D. HU B. HU C. ZHU F. LIU X. ZHANG J. WANG B. PENG Z. CLINICAL CHARACTERISTICS OF 138 HOSPITALIZED PATIENTS WITH 2019 NOVEL CORONAVIRUS-INFECT… | 669 | 777 |
| FANG L. KARAKIULAKIS G. ROTH M. ARE PATIENTS WITH HYPERTENSION AND DIABETES MELLITUS AT INCREASED RISK FOR COVID-19 INFECTION? (2020) | 624 | 1528 |
| HUANG C. WANG Y. LI X. REN L. ZHAO J. HU Y. ZHANG L. GU X. CLINICAL FEATURES OF PATIENTS INFECTED WITH 2019 NOVEL CORONAVIRUS IN WUHAN CHINA (2020) | 578 | 727 |
| MANCIA G. REA F. LUDERGNANI M. APOLONE G. CORRAO G. RENIN-ANGIOTENSIN-ALDOSTERONE SYSTEM BLOCKERS AND THE RISK OF COVID-19 (2020) | 571 | 1369 |
| ZHOU F. YU T. DU R. FAN G. LIU Y. LIU Z. XIANG J. GU X. CLINICAL COURSE AND RISK FACTORS FOR MORTALITY OF ADULT INPATIENTS WITH COVID-19 IN WUHAN C… | 563 | 687 |
| Knowledge Base 5: KB 5: unlabeled (n = 448, density =11.9) | ||
| HUANG C WANG Y LI X REN L ZHAO J HU Y CLINICAL FEATURES OF PATIENTS INFECTED WITH 2019 NOVEL CORONAVIRUS IN WUHAN CHINA (2020) | 1055 | 1081 |
| WANG D HU B HU C ZHU F LIU X ZHANG J CLINICAL CHARACTERISTICS OF 138 HOSPITALIZED PATIENTS WITH 2019 NOVEL CORONAVIRUS-INFECTED PNEUMONIA IN WUHAN … | 810 | 835 |
| WU Z MCGOOGAN JM. CHARACTERISTICS OF AND IMPORTANT LESSONS FROM THE CORONAVIRUS DISEASE 2019 (COVID-19) | 761 | 776 |
| GUO T FAN Y CHEN M WU X ZHANG L HE T CARDIOVASCULAR IMPLICATIONS OF FATAL OUTCOMES OF PATIENTS WITH CORONAVIRUS DISEASE 2019 (COVID-19) | 745 | 756 |
| ZHOU F YU T DU R FAN G LIU Y LIU Z CLINICAL COURSE AND RISK FACTORS FOR MORTALITY OF ADULT INPATIENTS WITH COVID-19 IN WUHAN CHINA: A RETROSPECTIVE… | 719 | 729 |
| SHI S QIN M SHEN B CAI Y LIU T YANG F ASSOCIATION OF CARDIAC INJURY WITH MORTALITY IN HOSPITALIZED PATIENTS WITH COVID-19 IN WUHAN CHINA (2020) | 707 | 717 |
| ZHENG YY MA YT ZHANG JY XIE X. COVID-19 AND THE CARDIOVASCULAR SYSTEM (2020) | 546 | 558 |
| HUANG C WANG Y LI X CLINICAL FEATURES OF PATIENTS INFECTED WITH 2019 NOVEL CORONAVIRUS IN WUHAN CHINA (2020) | 523 | 536 |
| WANG D HU B HU C CLINICAL CHARACTERISTICS OF 138 HOSPITALIZED PATIENTS WITH 2019 NOVEL CORONAVIRUS-INFECTED PNEUMONIA IN WUHAN CHINA (2020) | 493 | 503 |
| TANG N LI D WANG X SUN Z. ABNORMAL COAGULATION PARAMETERS ARE ASSOCIATED WITH POOR PROGNOSIS IN PATIENTS WITH NOVEL CORONAVIRUS PNEUMONIA (2020) | 443 | 458 |
In a co-cittion network, the strength of the relationship between a reference pair \(m\) and \(n\) (\(s_{m,n}^{coc}\)) is expressed by the number of publications \(C\) which are jointly citing reference \(m\) and \(n\).
\[s_{m,n}^{coc} = \sum_i c_{i,m} c_{i,n}\]
The intuition here is that references which are frequently cited together are likely to share commonalities in theory, topic, methodology, or context. It can be interpreted as a measure of similarity as evaluated by other researchers that decide to jointly cite both references. Because the publication process is time-consuming, co-citation is a backward-looking measure, which is appropriate to map the relationship between core literature of a field.
This is arguably the more interesting part. Here, we identify the
literature’s current knowledge frontier by carrying out a bibliographic
coupling analysis of the publications in our corpus. This measure uses
bibliographical information of publications to establish a similarity
relationship between them. Again, method details to be found in the tab
Technical description. As you will see, we identify the
main research area, but also a set of adjacent research areas with some
theoretical/methodological/application overlap.
To identify communities in the field’s knowledge frontier (labeled research areas) we again use the Lovain Algorithm (Blondel et al., 2008). We identify the following communities = research areas.
| label | AU | PY | TI | dgr_int | TC | TC_year |
|---|---|---|---|---|---|---|
| Research Area 1: RA 1: unlabeled (n = 469, density =1.72) | ||||||
| RA 1: unlabeled | TERPOS E;NTANASIS-STAT… | 2020 | HEMATOLOGICAL FINDINGS AND COMPLICATIONS OF COVID-19 | 21.31 | 871 | 435.50 |
| RA 1: unlabeled | LONG B;BRADY WJ;KOYFMA… | 2020 | CARDIOVASCULAR COMPLICATIONS IN COVID-19 | 20.01 | 412 | 206.00 |
| RA 1: unlabeled | STONE JH;FRIGAULT MJ;S… | 2020 | EFFICACY OF TOCILIZUMAB IN PATIENTS HOSPITALIZED WITH COVID-19 | 9.15 | 721 | 360.50 |
| RA 1: unlabeled | HERMINE O;MARIETTE X;T… | 2021 | EFFECT OF TOCILIZUMAB VS USUAL CARE IN ADULTS HOSPITALIZED WITH COVID-19 AND MODERATE OR SEVERE PNEUMONIA: A RANDOMIZED CL… | 15.62 | 416 | 416.00 |
| RA 1: unlabeled | MANCIA G;REA F;LUDERGN… | 2020 | RENIN–ANGIOTENSIN–ALDOSTERONE SYSTEM BLOCKERS AND THE RISK OF COVID-19 | 8.90 | 710 | 355.00 |
| RA 1: unlabeled | LALA A;JOHNSON KW;JANU… | 2020 | PREVALENCE AND IMPACT OF MYOCARDIAL INJURY IN PATIENTS HOSPITALIZED WITH COVID-19 INFECTION | 16.52 | 335 | 167.50 |
| RA 1: unlabeled | GANDHI RT;LYNCH JB;DEL… | 2020 | MILD OR MODERATE COVID-19 | 8.26 | 631 | 315.50 |
| RA 1: unlabeled | HE F;DENG Y;LI W | 2020 | CORONAVIRUS DISEASE 2019: WHAT WE KNOW? | 10.90 | 392 | 196.00 |
| RA 1: unlabeled | LECHIEN JR;CHIESA-ESTO… | 2020 | OLFACTORY AND GUSTATORY DYSFUNCTIONS AS A CLINICAL PRESENTATION OF MILD-TO-MODERATE FORMS OF THE CORONAVIRUS DISEASE (COVI… | 2.68 | 1411 | 705.50 |
| RA 1: unlabeled | GIUSTINO G;CROFT LB;ST… | 2020 | CHARACTERIZATION OF MYOCARDIAL INJURY IN PATIENTS WITH COVID-19 | 20.26 | 159 | 79.50 |
| Research Area 2: RA 2: unlabeled (n = 449, density =0.41) | ||||||
| RA 2: unlabeled | CEYSSENS L;VANELDEREN … | 2019 | BIOMECHANICAL RISK FACTORS ASSOCIATED WITH RUNNING-RELATED INJURIES: A SYSTEMATIC REVIEW | 5.62 | 72 | 24.00 |
| RA 2: unlabeled | CHAN ZYS;ZHANG JH;AU I… | 2018 | GAIT RETRAINING FOR THE REDUCTION OF INJURY OCCURRENCE IN NOVICE DISTANCE RUNNERS: 1-YEAR FOLLOW-UP OF A RANDOMIZED CONTRO… | 4.71 | 85 | 21.25 |
| RA 2: unlabeled | BERTELSEN ML;HULME A;P… | 2017 | A FRAMEWORK FOR THE ETIOLOGY OF RUNNING-RELATED INJURIES | 3.18 | 122 | 24.40 |
| RA 2: unlabeled | MESSIER SP;MARTIN DF;M… | 2018 | A 2-YEAR PROSPECTIVE COHORT STUDY OF OVERUSE RUNNING INJURIES: THE RUNNERS AND INJURY LONGITUDINAL STUDY (TRAILS) | 3.03 | 103 | 25.75 |
| RA 2: unlabeled | DAVIS IS;BOWSER BJ;MUL… | 2016 | GREATER VERTICAL IMPACT LOADING IN FEMALE RUNNERS WITH MEDICALLY DIAGNOSED INJURIES: A PROSPECTIVE INVESTIGATION | 2.02 | 145 | 24.17 |
| RA 2: unlabeled | RICE HM;JAMISON ST;DAV… | 2016 | FOOTWEAR MATTERS: INFLUENCE OF FOOTWEAR AND FOOT STRIKE ON LOAD RATES DURING RUNNING | 5.06 | 58 | 9.67 |
| RA 2: unlabeled | NAPIER C;MACLEAN CL;MA… | 2018 | KINETIC RISK FACTORS OF RUNNING-RELATED INJURIES IN FEMALE RECREATIONAL RUNNERS | 5.23 | 54 | 13.50 |
| RA 2: unlabeled | HULME A;NIELSEN RO;TIM… | 2017 | RISK AND PROTECTIVE FACTORS FOR MIDDLE- AND LONG-DISTANCE RUNNING-RELATED INJURY | 3.24 | 79 | 15.80 |
| RA 2: unlabeled | DAVIS IS;RICE HM;WEARI… | 2017 | WHY FOREFOOT STRIKING IN MINIMAL SHOES MIGHT POSITIVELY CHANGE THE COURSE OF RUNNING INJURIES | 4.71 | 47 | 9.40 |
| RA 2: unlabeled | FRANCIS P;WHATMAN C;SH… | 2019 | THE PROPORTION OF LOWER LIMB RUNNING INJURIES BY GENDER, ANATOMICAL LOCATION AND SPECIFIC PATHOLOGY: A SYSTEMATIC REVIEW | 3.51 | 63 | 21.00 |
| Research Area 3: RA 3: unlabeled (n = 443, density =0.12) | ||||||
| RA 3: unlabeled | WU L-H;ZHANG X-M;WANG … | 2018 | OCCURRENCE OF BISPHENOL S IN THE ENVIRONMENT AND IMPLICATIONS FOR HUMAN EXPOSURE: A SHORT REVIEW | 2.57 | 197 | 49.25 |
| RA 3: unlabeled | VALENTINO R;D’ESPOSITO… | 2016 | BISPHENOL A ENVIRONMENTAL EXPOSURE AND THE DETRIMENTAL EFFECTS ON HUMAN METABOLIC HEALTH: IS IT NECESSARY TO REVISE THE RI… | 1.80 | 64 | 10.67 |
| RA 3: unlabeled | WAN Y;HUO W;XU S;ZHENG… | 2018 | RELATIONSHIP BETWEEN MATERNAL EXPOSURE TO BISPHENOL S AND PREGNANCY DURATION | 2.29 | 50 | 12.50 |
| RA 3: unlabeled | DEFARGE N;SPIROUX DE V… | 2018 | TOXICITY OF FORMULANTS AND HEAVY METALS IN GLYPHOSATE-BASED HERBICIDES AND OTHER PESTICIDES | 0.61 | 164 | 41.00 |
| RA 3: unlabeled | DOCEA AO;GOFITA E;GOUM… | 2018 | SIX MONTHS EXPOSURE TO A REAL LIFE MIXTURE OF 13 CHEMICALS’ BELOW INDIVIDUAL NOAELS INDUCED NON MONOTONIC SEX-DEPENDENT BI… | 1.00 | 95 | 23.75 |
| RA 3: unlabeled | TSATSAKIS AM;DOCEA AO;… | 2019 | HORMETIC NEUROBEHAVIORAL EFFECTS OF LOW DOSE TOXIC CHEMICAL MIXTURES IN REAL-LIFE RISK SIMULATION (RLRS) IN RATS | 1.28 | 70 | 23.33 |
| RA 3: unlabeled | HERNÁNDEZ AF;GIL F;LAC… | 2017 | TOXICOLOGICAL INTERACTIONS OF PESTICIDE MIXTURES: AN UPDATE | 0.65 | 128 | 25.60 |
| RA 3: unlabeled | DOCEA AO;GOUMENOU M;CA… | 2019 | ADVERSE AND HORMETIC EFFECTS IN RATS EXPOSED FOR 12 MONTHS TO LOW DOSE MIXTURE OF 13 CHEMICALS: RLRS PART III | 1.46 | 57 | 19.00 |
| RA 3: unlabeled | GU J;ZHANG J;CHEN Y;WA… | 2019 | NEUROBEHAVIORAL EFFECTS OF BISPHENOL S EXPOSURE IN EARLY LIFE STAGES OF ZEBRAFISH LARVAE (DANIO RERIO) | 1.65 | 49 | 16.33 |
| RA 3: unlabeled | HERNÁNDEZ AF;TSATSAKIS AM | 2017 | HUMAN EXPOSURE TO CHEMICAL MIXTURES: CHALLENGES FOR THE INTEGRATION OF TOXICOLOGY WITH EPIDEMIOLOGY DATA IN RISK ASSESSMENT | 0.77 | 103 | 20.60 |
| Research Area 4: RA 4: unlabeled (n = 320, density =0.63) | ||||||
| RA 4: unlabeled | INCIARDI RM;ADAMO M;LU… | 2020 | CHARACTERISTICS AND OUTCOMES OF PATIENTS HOSPITALIZED FOR COVID-19 AND CARDIAC DISEASE IN NORTHERN ITALY | 3.60 | 281 | 140.50 |
| RA 4: unlabeled | ZHANG B;ZHOU X;QIU Y;S… | 2020 | CLINICAL CHARACTERISTICS OF 82 CASES OF DEATH FROM COVID-19 | 3.41 | 238 | 119.00 |
| RA 4: unlabeled | WU H;LARSEN CP;HERNAND… | 2020 | AKI AND COLLAPSING GLOMERULOPATHY ASSOCIATED WITH COVID-19 AND APOL1 HIGH-RISK GENOTYPE | 2.44 | 120 | 60.00 |
| RA 4: unlabeled | HANFF TC;HARHAY MO;BRO… | 2020 | IS THERE AN ASSOCIATION BETWEEN COVID-19 MORTALITY AND THE RENIN-ANGIOTENSIN SYSTEM? A CALL FOR EPIDEMIOLOGIC INVESTIGATIONS | 1.46 | 173 | 86.50 |
| RA 4: unlabeled | EVANS PC;ED RAINGER G;… | 2020 | ENDOTHELIAL DYSFUNCTION IN COVID-19: A POSITION PAPER OF THE ESC WORKING GROUP FOR ATHEROSCLEROSIS AND VASCULAR BIOLOGY, A… | 1.47 | 171 | 85.50 |
| RA 4: unlabeled | MAGLEBY R;WESTBLADE LF… | 2021 | IMPACT OF SEVERE ACUTE RESPIRATORY SYNDROME CORONAVIRUS 2 VIRAL LOAD ON RISK OF INTUBATION AND MORTALITY AMONG HOSPITALIZE… | 1.55 | 147 | 147.00 |
| RA 4: unlabeled | LANZA GA;DE VITA A;RAV… | 2021 | ELECTROCARDIOGRAPHIC FINDINGS AT PRESENTATION AND CLINICAL OUTCOME IN PATIENTS WITH SARS-COV-2 INFECTION | 7.55 | 24 | 24.00 |
| RA 4: unlabeled | DWECK MR;BULARGA A;HAH… | 2020 | GLOBAL EVALUATION OF ECHOCARDIOGRAPHY IN PATIENTS WITH COVID-19 | 0.83 | 183 | 91.50 |
| RA 4: unlabeled | KOTECHA T;KNIGHT DS;RA… | 2021 | PATTERNS OF MYOCARDIAL INJURY IN RECOVERED TROPONIN-POSITIVE COVID-19 PATIENTS ASSESSED BY CARDIOVASCULAR MAGNETIC RESONANCE | 1.39 | 107 | 107.00 |
| RA 4: unlabeled | ALOISIO E;CHIBIREVA M;… | 2020 | A COMPREHENSIVE APPRAISAL OF LABORATORY BIOCHEMISTRY TESTS AS MAJOR PREDICTORS OF COVID-19 SEVERITY | 4.13 | 36 | 18.00 |
| Research Area 5: RA 5: unlabeled (n = 310, density =0.66) | ||||||
| RA 5: unlabeled | LAN J;GE J;YU J;SHAN S… | 2020 | STRUCTURE OF THE SARS-COV-2 SPIKE RECEPTOR-BINDING DOMAIN BOUND TO THE ACE2 RECEPTOR | 1.58 | 2635 | 1317.50 |
| RA 5: unlabeled | SHANG J;YE G;SHI K;WAN… | 2020 | STRUCTURAL BASIS OF RECEPTOR RECOGNITION BY SARS-COV-2 | 1.31 | 1824 | 912.00 |
| RA 5: unlabeled | YUKI K;FUJIOGI M;KOUTS… | 2020 | COVID-19 PATHOPHYSIOLOGY: A REVIEW | 3.08 | 742 | 371.00 |
| RA 5: unlabeled | LUKASSEN S;CHUA RL;TRE… | 2020 | SARS-COV-2 RECEPTOR ACE2 AND TMPRSS2 ARE PRIMARILY EXPRESSED IN BRONCHIAL TRANSIENT SECRETORY CELLS | 3.39 | 537 | 268.50 |
| RA 5: unlabeled | GUPTA A;MADHAVAN MV;SE… | 2020 | EXTRAPULMONARY MANIFESTATIONS OF COVID-19 | 1.46 | 1154 | 577.00 |
| RA 5: unlabeled | MUNIYAPPA R;GUBBI S | 2020 | COVID-19 PANDEMIC, CORONAVIRUSES, AND DIABETES MELLITUS | 3.07 | 395 | 197.50 |
| RA 5: unlabeled | LIU PP;BLET A;SMYTH D;… | 2020 | THE SCIENCE UNDERLYING COVID-19: IMPLICATIONS FOR THE CARDIOVASCULAR SYSTEM | 2.65 | 439 | 219.50 |
| RA 5: unlabeled | BARNES BJ;ADROVER JM;B… | 2020 | TARGETING POTENTIAL DRIVERS OF COVID-19: NEUTROPHIL EXTRACELLULAR TRAPS | 1.54 | 749 | 374.50 |
| RA 5: unlabeled | BABAPOOR-FARROKHRAN S;… | 2020 | MYOCARDIAL INJURY AND COVID-19: POSSIBLE MECHANISMS | 5.07 | 204 | 102.00 |
| RA 5: unlabeled | AKHMEROV A;MARBÁN E | 2020 | COVID-19 AND THE HEART | 2.55 | 389 | 194.50 |
| Research Area 6: RA 6: unlabeled (n = 271, density =1.45) | ||||||
| RA 6: unlabeled | LIU J;LIU Y;XIANG P;PU… | 2020 | NEUTROPHIL-TO-LYMPHOCYTE RATIO PREDICTS CRITICAL ILLNESS PATIENTS WITH 2019 CORONAVIRUS DISEASE IN THE EARLY STAGE | 5.57 | 368 | 184.00 |
| RA 6: unlabeled | PHIPPS MM;BARRAZA LH;L… | 2020 | ACUTE LIVER INJURY IN COVID-19: PREVALENCE AND ASSOCIATION WITH CLINICAL OUTCOMES IN A LARGE U.S. COHORT | 11.54 | 153 | 76.50 |
| RA 6: unlabeled | WANG L;LI X;CHEN H;YAN… | 2020 | CORONAVIRUS DISEASE 19 INFECTION DOES NOT RESULT IN ACUTE KIDNEY INJURY: AN ANALYSIS OF 116 HOSPITALIZED PATIENTS FROM WUH… | 6.36 | 262 | 131.00 |
| RA 6: unlabeled | CAO Y;WEI J;ZOU L;JIAN… | 2020 | RUXOLITINIB IN TREATMENT OF SEVERE CORONAVIRUS DISEASE 2019 (COVID-19): A MULTICENTER, SINGLE-BLIND, RANDOMIZED CONTROLLED… | 5.90 | 256 | 128.00 |
| RA 6: unlabeled | TERSALVI G;VICENZI M;C… | 2020 | ELEVATED TROPONIN IN PATIENTS WITH CORONAVIRUS DISEASE 2019: POSSIBLE MECHANISMS | 8.20 | 177 | 88.50 |
| RA 6: unlabeled | XIONG Q;XU M;LI J;LIU … | 2021 | CLINICAL SEQUELAE OF COVID-19 SURVIVORS IN WUHAN, CHINA: A SINGLE-CENTRE LONGITUDINAL STUDY | 4.98 | 206 | 206.00 |
| RA 6: unlabeled | TETRO JA | 2020 | IS COVID-19 RECEIVING ADE FROM OTHER CORONAVIRUSES? | 3.72 | 275 | 137.50 |
| RA 6: unlabeled | LAI C-C;KO W-C;LEE P-I… | 2020 | EXTRA-RESPIRATORY MANIFESTATIONS OF COVID-19 | 6.96 | 141 | 70.50 |
| RA 6: unlabeled | POTERE N;VALERIANI E;C… | 2020 | ACUTE COMPLICATIONS AND MORTALITY IN HOSPITALIZED PATIENTS WITH CORONAVIRUS DISEASE 2019: A SYSTEMATIC REVIEW AND META-ANA… | 8.77 | 88 | 44.00 |
| RA 6: unlabeled | YANG X;JIN Y;LI R;ZHAN… | 2020 | PREVALENCE AND IMPACT OF ACUTE RENAL IMPAIRMENT ON COVID-19: A SYSTEMATIC REVIEW AND META-ANALYSIS | 8.90 | 85 | 42.50 |
| Research Area 7: RA 7: unlabeled (n = 250, density =0.23) | ||||||
| RA 7: unlabeled | MORITZ S;BARTZ-BEIELST… | 2017 | IMPUTETS: TIME SERIES MISSING VALUE IMPUTATION IN R | 1.87 | 310 | 62.00 |
| RA 7: unlabeled | BOBB JF;CLAUS HENN B;V… | 2018 | STATISTICAL SOFTWARE FOR ANALYZING THE HEALTH EFFECTS OF MULTIPLE CONCURRENT EXPOSURES VIA BAYESIAN KERNEL MACHINE REGRESSION | 1.20 | 190 | 47.50 |
| RA 7: unlabeled | MENTCH L;HOOKER G | 2016 | QUANTIFYING UNCERTAINTY IN RANDOM FORESTS VIA CONFIDENCE INTERVALS AND HYPOTHESIS TESTS | 1.05 | 101 | 16.83 |
| RA 7: unlabeled | KEIL AP;BUCKLEY JP;O’B… | 2020 | A QUANTILE-BASED G-COMPUTATION APPROACH TO ADDRESSING THE EFFECTS OF EXPOSURE MIXTURES | 0.75 | 142 | 71.00 |
| RA 7: unlabeled | AGIER L;PORTENGEN L;HY… | 2016 | A SYSTEMATIC COMPARISON OF LINEAR REGRESSION–BASED STATISTICAL METHODS TO ASSESS EXPOSOME-HEALTH ASSOCIATIONS | 1.02 | 104 | 17.33 |
| RA 7: unlabeled | SIROUX V;AGIER L;SLAMA R | 2016 | THE EXPOSOME CONCEPT: A CHALLENGE AND A POTENTIAL DRIVER FOR ENVIRONMENTAL HEALTH RESEARCH | 1.14 | 84 | 14.00 |
| RA 7: unlabeled | GAO M;KORTUM P;OSWALD F | 2018 | PSYCHOMETRIC EVALUATION OF THE USE (USEFULNESS, SATISFACTION, AND EASE OF USE) QUESTIONNAIRE FOR RELIABILITY AND VALIDITY | 1.71 | 54 | 13.50 |
| RA 7: unlabeled | LELIEVELD J;KLINGMÜLLE… | 2019 | CARDIOVASCULAR DISEASE BURDEN FROM AMBIENT AIR POLLUTION IN EUROPE REASSESSED USING NOVEL HAZARD RATIO FUNCTIONS | 0.22 | 384 | 128.00 |
| RA 7: unlabeled | AGUAYO GA;DONNEAU A-F;… | 2017 | AGREEMENT BETWEEN 35 PUBLISHED FRAILTY SCORES IN THE GENERAL POPULATION | 0.69 | 114 | 22.80 |
| RA 7: unlabeled | SCORNET E | 2016 | RANDOM FORESTS AND KERNEL METHODS | 0.96 | 82 | 13.67 |
| Research Area 8: RA 8: unlabeled (n = 201, density =1.16) | ||||||
| RA 8: unlabeled | FRÜHBECK G;CATALÁN V;R… | 2019 | ADIPONECTIN-LEPTIN RATIO IS A FUNCTIONAL BIOMARKER OF ADIPOSE TISSUE INFLAMMATION | 5.35 | 71 | 23.67 |
| RA 8: unlabeled | HEINDEL JJ;SKALLA LA;J… | 2017 | REVIEW OF DEVELOPMENTAL ORIGINS OF HEALTH AND DISEASE PUBLICATIONS IN ENVIRONMENTAL EPIDEMIOLOGY | 4.42 | 73 | 14.60 |
| RA 8: unlabeled | TIAN Y;SU L;WANG J;DUA… | 2018 | FRUIT AND VEGETABLE CONSUMPTION AND RISK OF THE METABOLIC SYNDROME: A META-ANALYSIS | 5.07 | 62 | 15.50 |
| RA 8: unlabeled | CARDET JC;ASH S;KUSA T… | 2016 | INSULIN RESISTANCE MODIFIES THE ASSOCIATION BETWEEN OBESITY AND CURRENT ASTHMA IN ADULTS | 5.38 | 56 | 9.33 |
| RA 8: unlabeled | LUO Y;MA X;SHEN Y;XU Y… | 2017 | NECK CIRCUMFERENCE AS AN EFFECTIVE MEASURE FOR IDENTIFYING CARDIO-METABOLIC SYNDROME: A COMPARISON WITH WAIST CIRCUMFERENCE | 5.74 | 50 | 10.00 |
| RA 8: unlabeled | MAZIDI M;KENGNE A-P;KA… | 2018 | LIPID ACCUMULATION PRODUCT AND TRIGLYCERIDES/GLUCOSE INDEX ARE USEFUL PREDICTORS OF INSULIN RESISTANCE | 4.66 | 60 | 15.00 |
| RA 8: unlabeled | CHUNG HS;HWANG SY;CHOI… | 2018 | IMPLICATIONS OF CIRCULATING METEORIN-LIKE (METRNL) LEVEL IN HUMAN SUBJECTS WITH TYPE 2 DIABETES | 6.23 | 37 | 9.25 |
| RA 8: unlabeled | BEYDOUN MA;CHEN X;JHA … | 2019 | CAROTENOIDS, VITAMIN A, AND THEIR ASSOCIATION WITH THE METABOLIC SYNDROME: A SYSTEMATIC REVIEW AND META-ANALYSIS | 3.85 | 55 | 18.33 |
| RA 8: unlabeled | LACLAUSTRA M;MORENO-FR… | 2019 | IMPAIRED SENSITIVITY TO THYROID HORMONES IS ASSOCIATED WITH DIABETES AND METABOLIC SYNDROME | 4.80 | 35 | 11.67 |
| RA 8: unlabeled | CǍTOI AF;PÂRVU AE;ANDR… | 2018 | METABOLICALLY HEALTHY VERSUS UNHEALTHY MORBIDLY OBESE: CHRONIC INFLAMMATION, NITRO-OXIDATIVE STRESS, AND INSULIN RESISTANCE | 4.44 | 35 | 8.75 |
In a bibliographic coupling network, the coupling-strength between publications is determined by the number of commonly cited references they share, assuming a common pool of references to indicate similarity in context, methods, or theory. Formally, the strength of the relationship between a publication pair \(i\) and \(j\) (\(s_{i,j}^{bib}\)) is expressed by the number of commonly cited references.
\[s_{i,j}^{bib} = \sum_m c_{i,m} c_{j,m}\]
Since our corpus contains publications which differ strongly in terms of the number of cited references, we normalize the coupling strength by the Jaccard similarity coefficient. Here, we weight the intercept of two publications’ bibliography (shared refeences) by their union (number of all references cited by either \(i\) or \(j\)). It is bounded between zero and one, where one indicates the two publications to have an identical bibliography, and zero that they do not share any cited reference. Thereby, we prevent publications from having high coupling strength due to a large bibliography (e.g., literature surveys).
\[S_{i,j}^{jac-bib} =\frac{C(i \cap j)}{C(i \cup j)} = \frac{s_{i,j}^{bib}}{c_i + c_j - s_{i,j}^{bib}}\]
More recent articles have a higher pool of possible references to co-cite to, hence they are more likely to be coupled. Consequently, bibliographic coupling represents a forward looking measure, and the method of choice to identify the current knowledge frontier at the point of analysis.
All results are preliminary so far…